850 research outputs found

    Hospital financing of ischaemic stroke : determinants of funding and usefulness of DRG subcategories based on severity of illness

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    Background: Several Western and Arab countries, as well as over 30 States in the US are using the "All-Patient Refined Diagnosis-Related Groups" (APR-DRGs) with four severity-of-illness (SOI) subcategories as a model for hospital funding. The aim of this study is to verify whether this is an adequate model for funding stroke hospital admissions, and to explore which risk factors and complications may influence the amount of funding. Methods: A bottom-up analysis of 2496 ischaemic stroke admissions in Belgium compares detailed in-hospital resource use (including length of stay, imaging, lab tests, visits and drugs) per SOI category and calculates total hospitalisation costs. A second analysis examines the relationship between the type and location of the index stroke, medical risk factors, patient characteristics, comorbidities and in-hospital complications on the one hand, and the funding level received by the hospital on the other hand. This dataset included 2513 hospitalisations reporting on 35,195 secondary diagnosis codes, all medically coded with the International Classification of Disease (ICD-9). Results: Total costs per admission increased by SOI ((sic)3710-(sic)16,735), with severe patients costing proportionally more in bed days (86%), and milder patients costing more in medical imaging (24%). In all resource categories (bed days, medications, visits and imaging and laboratory tests), the absolute utilisation rate was higher among severe patients, but also showed more variability. SOI 1-2 was associated with vague, non-specific stroke-related ICD-9 codes as primary diagnosis (71-81% of hospitalisations). 24% hospitalisations had, in addition to the primary diagnosis, other stroke-related codes as secondary diagnoses. Presence of lung infections, intracranial bleeding, severe kidney disease, and do-not-resuscitate status were each associated with extreme SOI (p < 0.0001). Conclusions: APR-DRG with SOI subclassification is a useful funding model as it clusters stroke patients in homogenous groups in terms of resource use. The data on medical care utilisation can be used with unit costs from other countries with similar healthcare set-ups to 1) assess stroke-related hospital funding versus actual costs; 2) inform economic models on stroke prevention and treatment. The data on diagnosis codes can be used to 3) understand which factors influence hospital funding; 4) raise awareness about medical coding practices

    Genetics of Atrial Fibrillation and Possible Implications for Ischemic Stroke

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    Atrial fibrillation is the most common cardiac arrhythmia mainly caused by valvular, ischemic, hypertensive, and myopathic heart disease. Atrial fibrillation can occur in families suggesting a genetic background especially in younger subjects. Additionally recent studies have identified common genetic variants to be associated with atrial fibrillation in the general population. This cardiac arrhythmia has important public health implications because of its main complications: congestive heart failure and ischemic stroke. Since atrial fibrillation can result in ischemic stroke, one might assume that genetic determinants of this cardiac arrhythmia are also implicated in cerebrovascular disease. Ischemic stroke is a multifactorial, complex disease where multiple environmental and genetic factors interact. Whether genetic variants associated with a risk factor for ischemic stroke also increase the risk of a particular vascular endpoint still needs to be confirmed in many cases. Here we review the current knowledge on the genetic background of atrial fibrillation and the consequences for cerebrovascular disease

    Smart Solutions: Smart Grid Demokit

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    Treball desenvolupat dins el marc del programa 'European Project Semester'.The purpose of this report is to justify the design choices of the smart grid demo kit. Something had to be designed to make a smart grid clear for people who have little knowledge about smart grids. The product had to be appealing and clear for people to understand. And eventually should be usable, for example, on an information market. The first part of the research consisted of looking how to shape the whole system. How the 'tiles' had to look to be interactive for users and what they should feature. One part of this was doing research to get to know more about the already existing knowledge amount users. Another research investigated what appeals the most to the users. After this, a concept was created in compliance with the group and the client. The concept consists of hexagonal tiles, each with a different function: houses, solar panels, wind turbines, factories and energy storages. These tiles are all different parts of a smart grid. When combining these tiles, it can be made clear to users how smart grids work. The tiles are fabricated using a combination of 3D printing and laser cutting. The tiles have laser cut symbols on top of them to show what part of the smart grid they are. Digital LED strips are on top of the tiles to show the direction of the energy flow, and the colors indicate if the tile is producing or consuming power from the grid. The tiles are connected to each other by the so called “grid blocks”. These blocks make up the central power grid and are also lighting up by LED strips. Each tile is equipped with a microcontroller which controls the LED strips and makes it possible for the different tiles to “talk” with each other. Using this, the central tile knows which tiles are connected to the system. The central tile controls all tiles and runs the simulation of the smart grid. For further development of the project, it can be investigated how to control and adjust the system from an external system, for example by a tablet. The final product consists of five tiles connected by seven grid blocks which show how a smart grid works

    Innovative Approaches for Manufacturing Epoxy-Modified Wood and Cellulose Fiber Composites:A Comparison between Injection Molding and 3D Printing

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    The current study focused on improving the properties of polylactic acid (PLA) for wider application in load-bearing scenarios. Various methods were explored to optimize the interaction between PLA and natural fibers, particularly wood fibers (WFs). Alkalized and epoxy-impregnated WFs were evaluated against untreated WFs and cellulose fibers in both injection molding (IM) and fused deposition modeling (FDM). FTIR analysis revealed the removal of hemicellulose and lignin in alkalized WFs and uniform epoxy curing. Addition of fibers reduced PLA's thermal stability while acting as nucleating agents. Additionally, fibers augmented the storage modulus of biocomposites, with alkalized fibers exhibiting the highest tensile modulus in IM. FDM samples with a 0° raster angle showed superior impact resistance compared to IM counterparts. Moreover, raster angle significantly influenced FDM biocomposite properties, enhancing the tensile strength and modulus of untreated WF and cellulose fibers at 0°. Although FDM did not produce alkalized WF samples, epoxy impregnation emerged as a promising method for enhancing PLA/WF composite mechanical properties in the IM process, offering valuable insights for composite material development.</p

    MicroMHiDe: A Multispectral Sub-Meter Resolution Payload for SmallSats

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    The Earth Observation market has been going through a complete mutation during the last decade with the deployment of constellations of nano- and smallsats. These can offer shorter revisit time and capture relevant information for specific applications, and this for a significantly lower cost

    Innovative Approaches for Manufacturing Epoxy-Modified Wood and Cellulose Fiber Composites:A Comparison between Injection Molding and 3D Printing

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    The current study focused on improving the properties of polylactic acid (PLA) for wider application in load-bearing scenarios. Various methods were explored to optimize the interaction between PLA and natural fibers, particularly wood fibers (WFs). Alkalized and epoxy-impregnated WFs were evaluated against untreated WFs and cellulose fibers in both injection molding (IM) and fused deposition modeling (FDM). FTIR analysis revealed the removal of hemicellulose and lignin in alkalized WFs and uniform epoxy curing. Addition of fibers reduced PLA's thermal stability while acting as nucleating agents. Additionally, fibers augmented the storage modulus of biocomposites, with alkalized fibers exhibiting the highest tensile modulus in IM. FDM samples with a 0° raster angle showed superior impact resistance compared to IM counterparts. Moreover, raster angle significantly influenced FDM biocomposite properties, enhancing the tensile strength and modulus of untreated WF and cellulose fibers at 0°. Although FDM did not produce alkalized WF samples, epoxy impregnation emerged as a promising method for enhancing PLA/WF composite mechanical properties in the IM process, offering valuable insights for composite material development.</p

    Electrocardiographic RR Interval Dynamic Analysis to Identify Acute Stroke Patients at High Risk for Atrial Fibrillation Episodes During Stroke Unit Admission

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    Patients at short-term risk of paroxysmal atrial fibrillation (PAF) often exhibit increased RR interval variability during sinus rhythm. We studied if RR dynamic analysis, applied in the first hours after stroke unit (SU) admission, identified acute ischemic stroke patients at higher risk for subsequent PAF episodes detected within the SU hospitalization. Acute ischemic stroke patients underwent continuous cardiac monitoring (CCM) using standard bedside monitors immediately after SU admission. The CCM tracks from the first 48\ua0h were analyzed using a telemedicine service (SRA clinic, Apoplex Medical, Germany). Based on the RR dynamics, the stroke risk analysis (SRA) algorithm stratified the risk for PAF as follows: low risk for PAF, high risk for PAF, presence of manifest AF. The subsequent presence/absence of PAF during the whole SU hospitalization was ruled out using all available CCMs, standard ECGs, or 24-h Holter ECGs. Two hundred patients (40% females, mean age 71\u2009\ub1\u200916\ua0years) were included. According to the initial SRA analysis, 111 patients (56%) were considered as low risk for PAF, 52 (26%) as high risk while 37 patients (18%) had manifest AF. A low-risk level SRA was associated with a reduced probability for subsequent PAF detection (1/111, 0.9%, 95% CI 0-4.3%) while a high-risk level SRA predicted an increased probability (20/52, 38.5% (95% CI 25-52%). RR dynamic analysis performed in the first hours after ischemic stroke may stratify patients into categories at low or high risk for forthcoming paroxysmal AF episodes detected within the SU hospitalization

    Secure Latent Dirichlet Allocation

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    Topic modelling refers to a popular set of techniques used to discover hidden topics that occur in a collection of documents. These topics can, for example, be used to categorize documents or label text for further processing. One popular topic modelling technique is Latent Dirichlet Allocation (LDA). In topic modelling scenarios, the documents are often assumed to be in one, centralized dataset. However, sometimes documents are held by different parties, and contain privacy- or commercially-sensitive information that cannot be shared. We present a novel, decentralized approach to train an LDA model securely without having to share any information about the content of the documents with the other parties. We preserve the privacy of the individual parties using a combination of privacy enhancing technologies. We show that our decentralized, privacy preserving LDA solution has a similar accuracy compared to an (insecure) centralised approach. With 10241024-bit Paillier keys, a topic model with 55 topics and 30003000 words can be trained in around 1616 hours. Furthermore, we show that the solution scales linearly in the total number of words and the number of topics

    Demonstration of asymmetric electron conduction in pseudosymmetrical photosynthetic reaction centre proteins in an electrical circuit

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    Photosynthetic reaction centres show promise for biomolecular electronics as nanoscale solar-powered batteries and molecular diodes that are amenable to atomic-level re-engineering. In this work the mechanism of electron conduction across the highly tractable Rhodobacter sphaeroides reaction centre is characterized by conductive atomic force micro-scopy. We find, using engineered proteins of known structure, that only one of the two cofactor wires connecting the positive and negative termini of this reaction centre is capable of conducting unidirectional current under a suitably oriented bias, irrespective of the magnitude of the bias or the applied force at the tunnelling junction. This behaviour, strong functional asymmetry in a largely symmetrical protein–cofactor matrix, recapitulates the strong functional asymmetry characteristic of natural photochemical charge separation, but it is surprising given that the stimulus for electron flow is simply an externally applied bias. Reasons for the electrical resistance displayed by the so-called B-wire of cofactors are explored

    Factors determining human-to-human transmissibility of zoonotic pathogens via contact.

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    The pandemic potential of zoonotic pathogens lies in their ability to become efficiently transmissible amongst humans. Here, we focus on contact-transmitted pathogens and discuss the factors, at the pathogen, host and environmental levels that promote or hinder their human-to-human transmissibility via the following modes of contact transmission: skin contact, sexual contact, respiratory contact and multiple route contact. Factors common to several modes of transmission were immune evasion, high viral load, low infectious dose, crowding, promiscuity, and co-infections; other factors were specific for a pathogen or mode of contact transmission. The identification of such factors will lead to a better understanding of the requirements for human-to-human spread of pathogens, as well as improving risk assessment of newly emerging pathogens
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